In this thesis, a method of optimization of nonuniform pulse repetition interval for pulse Doppler radars is investigated. PRI jittering technique is used for the selection of inter-pulse intervals. An environment with white Gaussian noise and clutter interference is defined and applying generalized likelihood ratio test, a sufficient statistic function for the detection of the target is derived. The effect of jitter set selection on range and Doppler ambiguity resolution and clutter rejection is investigated. Jitter sets for Doppler ambiguity resolution are investigated by the minimization of the sufficient statistic function value at other estimated target velocities. Jitter sets for range ambiguity resolution are investigated by minimization of the number of ambigous hits at other estimated ranges. The clutter rejection properties of jitter sets are evaluated by defining a constraint function on zero velocity clutter rejection. The problems stated are solved using MATLAB with genetic algorithms. It is observed that there is a trade off between Doppler ambiguity resolution and clutter rejection properties of jitter sets. Low jitter values are needed for good clutter rejection. The performance of jitter sets are optimized according to range ambiguity resolution and clutter rejection properties by defining cost functions. It is observed that good range ambiguity resolution and clutter rejection can be achieved by an optimized PRI jittering technique. Finally, the effects of quantization of Doppler filter coefficients and target returns using improvement factor as the performance criterion are evaluated.

This thesis considers the filtering and prediction problems of nonlinear noisy econometric systems. As a filter/predictor, the standard tool Extended Kalman Filter and new approaches Discrete Quantization Filter and Sequential Importance Resampling Filter are used. The algorithms are compared by using Monte Carlo Simulation technique. The advantages of the new algorithms over Extended Kalman Filter are shown.

In this study, a dynamic resource management and subscriber profile prediction scheme for mobile communication systems is presented. The aim is to achieve a high level of QoS for both handoff calls and new calls, while at the same time to improve the utilization of wireless network resources. The simultaneous satisfaction of these two actually conflicting interests will be thanks to two major key features. First, it will be due to the individual subscriber profile based prior information about handoff reservation requests that are provided by the mobile terminals. This information is based on the cell transition probabilities calculated by the mobile itself using collected information during past operations. Second, it will be due to a two-way approach implemented in the resource management processes. The two-way approach controls both the amount of reserved radio channels and the new call admission in a dynamic way, depending on the subscriber mobility and network traffic conditions.

In radars, matched filters are used in the receiver of the system. Since the target velocity is not known a priori, degradation occurs due to mismatch of the return signal and the matched filter. The performance of the radar can be improved by using a bank of matched filters. The first topic investigated in this work is optimization of the bank of matched filter structure. Two methods are proposed for the design of the parallel filter structure and computations are performed with both methods. The output signal of a radar receiver filter consists not only of the main peak from the target but also of range sidelobes. In a multi-target radar environment, the sidelobes of one large target may appear as a smaller target at another range, or the integrated sidelobes from targets or clutter may mask all the information of another target. The second part of this thesis discusses the methods for decreasing the sidelobe level of the receiver output. Two methods are studied for this purpose. The first is the classical amplitude weighting and the second is the use of an inverse filter that minimizes total sidelobe energy. Both methods decrease the sidelobe levels while bringing a mismatch loss and main peak broadening. For the inverse filter case it is observed that the effect of inverse filter becomes evident as the filter length is increased beyond some point. Finally, the effects of quantization on video signal and the receiver filter coefficients are evaluated. It is observed that 16 bits quantization is sufficient for all kinds of receiver filters tested.

Orthogonal Frequency Division Multiplexing (OFDM) and Single Carrier Block Transmissions (SCBT) are located at the two opposite edges of block transmission concept. In this thesis a system which lies between OFDM and SCBT is proposed. The new system, namely Block Transmissions on Orthogonal Carriers (BTOC), can be considered as a hybrid form of OFDM and SCBT. BTOC system is investigated under the redundant filterbank precoders and equalizers framework. Peak to average power ratio (PAPR) of BTOC is formulated and compared with the PAPRs of OFDM and SCBT. Effect of frequency offset for BTOC is investigated and comparison between OFDM, SCBT, and BTOC is presented. Simulation results of Zero Padded OFDM (ZP-OFDM), SCBT, and BTOC are included.

Sum-product algorithm can be employed for obtaining the marginal probability density functions from a given joint probability density function (p.d.f.). The sum-product algorithm operates on a factor graph which represents the dependencies of the random variables whose joint p.d.f. is given. The sum-product algorithm can not be operated on factor-graphs that contain loops. For these factor graphs iterative sum-product algorithm is used. A factor graph which contains loops can be divided in to loop-free sub-graphs. Sum-product algorithm can be operated in these loop-free sub-graphs and results of these sub-graphs can be combined for obtaining the result of the whole factor graph in an iterative manner. This method may increase the convergence rate of the algorithm significantly while keeping the complexity of an iteration and accuracy of the output constant. A useful by-product of this research that is introduced in this thesis is a good approximation to message calculation in factor nodes of the inter-symbol interference (ISI) factor graphs. This approximation has a complexity that is linearly proportional with the number of neighbors instead of being exponentially proportional. Using this approximation and the sub-graph idea we have designed and simulated joint decoding-equalization (turbo equalization) algorithm and obtained good results besides the low complexity.

In this study, possible applications of label switching in large area, fully optical networks are investigated. The objective was to design a label assignment method by using Generalized Multi-Protocol Label Switching (GMPLS) concept to get an efficient optical network operation. In order to fulfill this objective, two new approaches were proposed: a label assignment method and a concatenated label structure. Label assignment method was designed to provide an efficient utilization of resources. Concatenated label structure aimed handling the label in optical domain. Mainly, the lambda switch capable GMPLS networks were investigated. In order to verify the performance of label assignment method, a simulator was developed. The results of simulation have clearly indicated that the proposed approaches could be beneficial in an optical network operation.

A proper time-frequency transform technique suppresses the blurring and smearing effect of the time-varying Doppler shift on the target image. The conventional target imaging method uses the Fourier transform for extracting the Doppler shift from the received radar pulse. Since the Doppler shift is timevarying for rotating targets, the constructed images will be degraded. In this thesis, the Doppler shift information required for the Range-Doppler image of the target is extracted by using high resolution time-frequency transform techniques. The Wigner-Ville Distribution and the Adaptive Gabor Representation with the Coarse-to-Fine and the Matching Pursuit Search Algorithms are examined techniques for the target imaging system. The modified Matching Pursuit Algorithm, the Matching Pursuit with Reduced Dictionary is proposed which decreases the signal processing time required by the Adaptive Gabor Representation. The Hybrid Matching Pursuit Search Algorithm is also introduced in this thesis work and the Coarse-to-Fine Algorithm and the Matching Pursuit Algorithm are combined for obtaining better representation quality of a signal in the time-frequency domain. The stated techniques are applied on to the sample signals and compared with each other. The application of these techniques in the target imaging system is also performed for the simulated aircrafts.

The goal of this thesis study is to investigate the Ambiguity Function Technique for target detection in phase-coded continuous wave radar. Also, phase shift keying techniques are examined in detail. Continuous Wave (CW) Radars, which are also known as Low Probability of Intercept (LPI) radars, emit continuous signals in time which are modulated by either frequency modulation or phase modulation techniques. Modulation of the transmitted radar signal is needed to estimate both the range and the radial velocity of the detected targets. In this thesis, Phase Shift Keying (PSK) techniques such as the Barker codes, Frank codes, P1, P2, P3, P4 codes will be employed for radar signal modulation. The use of Ambiguity Function, which is a non-linear Time- Frequency Representation (TFR), for target detection will be investigated in phasecoded CW radars for different target scenarios.

This thesis analyzes the process of deblurring of degraded images generated by space-variant nonlinear image systems with Gaussian observation noise. The restoration of blurred images is performed by using two methods / a modified version of the Optimum Decoding Based Smoothing Algorithm and the Bootstrap Filter Algorithm which is a version of Particle Filtering methods. A computer software called MATLAB is used for performing the simulations of image estimation. The results of some simulations for various observation and image models are presented.